Visual Tracking in Image Streams Acquired by Static Cameras Based on Change Detection by Raspberry Pi G

ISSN 2319-8885 Vol.05,Issue.28 September-2016,

Pages:5985-5990

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Visual Tracking in Image Streams Acquired by Static Cameras Based on Change Detection by Raspberry Pi G. PRAVEEN1, K. HARI2, VENTRAPRAGADA TEJU3 1PG Scholar, Dept of ECE(ES), Jawaharlal Nehru Institute of Technology, Ibrahimpatnam, Hyderabad, TS, India. 2Assistant Professor, Dept of ECE, Jawaharlal Nehru Institute of Technology, Ibrahimpatnam, Hyderabad, TS, India. 3Associate Professor, Dept of ECE, Jawaharlal Nehru Institute of Technology, Ibrahimpatnam, Hyderabad, TS, India.

Abstract: Visual tracking in image streams acquired by static cameras is usually based on change detection and recursive Bayesian estimation, such an approach laying at the core of many practical applications. Yet, the interaction between the change detector and the Bayesian filter is typically designed. Differently, this paper develops a sound framework to model and implement a bidirectional communication flow between the two processes. In our Bayesian loop, change detection provides

well defined observation likelihood to the recursive filter and the filter prediction provides an informative prior to the change detector, which deploys Bayesian reasoning alike. The loop is developed for the two major variants of Bayesian filters used in tracking, namely the Kalman filter and the particle filter. Experiments on publicly available videos and a novel challenging data set show that the proposed interaction scheme outperforms several state-of-the-art trackers.

Keywords: Image Sequence Analysis, Kalman Filters, Motion Detection, Particle Filters Real-Time Tracking, Video Surveillance, Video Tracking.

I. INTRODUCTION Bayesian reasoning has been used also to solve the Today‟s Automobiles, invariably comply with digital problem of Change Detection(CD) in image sequences, and control systems as a consequence of constant growth in CD is at the root of many proposals in visual tracking. technology. Recent Vehicles contains large number of Nonetheless, interaction between the change detection and Electronic Control Systems and already there are large tracking modules is usually modeled heuristically. This numbers of Electronic Control Units present. The growth of negatively affects the quality of the information flowing automotive electronics is the result parties of the customers between the two computational levels, as well as the wish for better safety and greater comfort and also for other soundness of proposals. Furthermore, the interaction can be requirements like improved emission control and reduced highly influenced by heuristically hand-tuned parameters, fuel consumption. Visual tracking in image streams acquired such as CD thresholds. Hence, a first original contribution of by static cameras is usually based on change detection and this paper is a theoretically grounded and almost parameters- recursive Bayesian estimation, such an approach laying at the free approach to provide an observation likelihood to the core of many practical applications. Yet, the interaction RBE tracker from the posterior obtained by a Bayesian between the change detector and the Bayesian filter is Change Detection (BCD). The transmission rate of this typically designed heuristically. Differently, this paper device is 9600 baud with the duration of start bit and each develops a sound framework to model and implement a subsequent bit is about 0.104ms. The complete character bidirectional communication flow between the two processes. frame of 11 bits is transmitted in 1.146ms. MAX 232 IC In our Bayesian loop, change detection provides well defined mounted on the master board converts the 0‟s and 1‟s to TTL observation likelihood to the recursive filter and the filter logic. ZIGBEE module uses direct sequence spread spectrum prediction provides an informative prior to the change (DSSS) mechanism for the data encryption and the frequency detector, which deploys Bayesian reasoning alike. The loop will be 2.4GHz. The Zigbee module uses carrier sense is developed for the two major variants of Bayesian filters multiple access collision avoidance mechanism (CSMA/CA) used in tracking, namely the Kalman filter and the particle for the data transfer between two modules. The Raspberry pi filter. Experiments on publicly available videos and a novel is a low cost credit card sized Linux computer which has the challenging data set show that the proposed interaction ability to interact with the outside world and has been used in scheme outperforms several state-of-the-art trackers a wide array of digital maker projects. An open source Recursive Bayesian Estimation (RBE) casts visual tracking operating system that uses Linux kernel called Debian is used as a Bayesian inference problem in state space given noisy on the embedded Raspberry Pi device in an operating system observation of the hidden state. called Raspberry.

Copyright @ 2016 IJSETR. All rights reserved. G. PRAVEEN, K. HARI, VENTRAPRAGADA TEJU Linux kernel has been ported to variety of CPUs which communication between the master and raspberry pi is wired are used not only for computers but also for ARC, ARM, and the raspberry pi can be operated through remote AVR32, ETRAX CRIS, FR – V, H8300, IP7000, m68k, computing either wired or wireless. The communication PowerPC, Super H and Xtensa processors A printed circuit between the master and raspberry pi is wired and the board (PCB) uses conductive tracks, pads and other features raspberry pi can be operated through remote computing etched from copper sheets to connect the electronic either wired or wireless. The on– field firmware up gradation components laminated onto a non-conductive substrate. of master and slave is possible without removing or Surface – mount technology (SMT) is a technique where the disconnecting any devices from the module with the help of components are placed directly onto the surface of printed USB boot loader feature in microcontroller. circuit boards (PCBs),Both technologies can be used in a combination i.e. the components that cannot be mounted can be used with through hole technology.

Fig.2. snap shot of transmitter side kit.

The entire module functionality is controlled by the Fig.1. Block diagram of the process monitoring system raspberry pi. One of the major future enhancements of this using Raspberry pi. master module is the in-built USB to UART converter which can directly communicate with the android devices without In industrial automation, there are different manufactures using any other driver software or hardware. The raspberry pi producing their own PLCs. The PLCs in an industry is processor runs in 3.3V. So the master module has in-built connected with distributed control system (DCS) by MOSFET based 3.3V to 5V voltage level shifter circuit. No protocols such as RS232/485, USB and Ethernet. The DCS bridging hardware is required as the raspberry pi can directly has multi-level hierarchical network structure for communicate with the master module. A TTL to RS232 level communication. Due to the hierarchical network structure, shifter is used to communicate with any other hardware that the communication becomes complex and high in cost. accepts RS232 protocol. Slave Module contains the sensor Complete network from field level to control level is not interfacing of physical parameters like Temperature, Light formed. The java simulators can be used as front end panel intensity and vibration level identifier sensors. Data acquired for monitoring and control. The java servers used to control from each parameter is collected in Slave and sent to Master the process in a fiel. Internet of Things (IoT) is a fast module through zigbee transmission. The relay and alarm are developing technology that connects all devices with internet. also connected to the microcontroller for controlling purpose. For soft real time systems TCP, UDP and IP protocols are The MAX232 is responsible for converting parallel data into efficient. Embedded web server and Linux based system is addressed serial data and vice versa. cost effective with high performance. The RS232 protocol is sufficient for parameter monitoring and control. The master III. HARDWARE DESCRIPTION slave architecture gives good performance in real time The production Raspberry Pi board has a 26-pin 2.54 control applications. The graphical language is efficient for mm (100 mil) expansion header, marked as P1, arranged in development of front end and back end panels for process a 2x13 strip. They provide 8 GPIO pins plus access to I²C, monitoring and control as shown in Fig.1. SPI, UART), as well as +3.3 V, +5 V and GND supply lines. Pin one is the pin in the first column and on the II. SYSTEM DESCRIPTION bottom row. The Fig. 2 shows the system that is designed with both wireless slaves and wireless master where the communication Transmitter Section: is a half-duplex communication. The master module acts a We investigate Bayesian visual tracking based on change bridge device between slaves and the raspberry pi computer. detection as shown in Fig.3. Although in many proposals The master can also communicate with any android devices change detection is key for tracking, little attention has been and compactable with all X86, X64 and ARM architectures paid to sound modeling of the interaction between the change that runs any operating system with RS232 functionality. The detector and the tracker. In this work, we develop a International Journal of Scientific Engineering and Technology Research Volume.05, IssueNo.28, September-2016, Pages: 5985-5990 Visual Tracking in Image Streams Acquired by Static Cameras based on Change Detection by Raspberry Pi principled framework whereby both processes can virtuously of prevalent calculations in light of factual per pixel influence each other according to a Bayesian loop: change foundation models, for example, blend of Gaussians or detection provides completely specified observation portion based nonparametric models, are powerful in the likelihood to the tracker and the tracker provides an event that of commotion and steady brightening changes informative prior to the change detector. (e.g., due to the time) as shown in Fig.4. Sadly, however, they can't manage those bothers bringing about sudden force changes (e.g., a light switch), yielding in such cases numerous false positives. A menial of calculations depends on from the earlier displaying the conceivable spurious power changes over little picture patches yielded by bothers. Tailing this thought, a pixel from the current casing is delegated changed, if the force changes between its nearby neighborhood and the relating neighborhood out of sight can't be clarified by the picked from the earlier model. Therefore, continuous and also sudden photometric contortions don't yield false positives on the off chance that they are clarified by the model. Along these lines, the principle issue concerns the decision of the from the earlier.

Fig.3. Transmitter Section. Receiver Section:

Fig.5. Receiver Section.

ZigBee is an emerging wireless communication technology as shown in Fig.5. It has several advantages over other existing wireless communication technologies which make it a better choice for multiple nodes as shown in Fig.6.

Fig.6. Zigbee module.

Fig.4. GPIO connection on Rpi. These advantages of zigbee are as follows: By using camera the system will capture the picture  Low-cost device compared to others initially and this picture information will be saved as data.  Less complexity for the users When the next picture is captured by the camera the picture is  Flexibility for expansion in future compared with the data already stored in memory. This  Possibility for multipoint interconnections comparison performed by the raspberry pi using kalman  Possibility of direct connection to any sensor, meter and filters. If the same data is captured then the indication of  Actuator in long distance intruder found will be sent to the receiver by using zigbee  Possibility of using encryption codes for enhancing the technology, at receiver section we can also get the exact System security. location of the intruder by using Global Positioning System.  Possibility of developing codes to prevent interference The principle trouble with change identification comprises in with other wireless communication signals. recognizing changes of the scene in nearness of spurious  Low consumption device and therefore suitable for force varieties yielded by disturbances, for example, weather monitoring stations that are usually in remote commotion, progressive, or sudden light changes, dynamic areas; modification of camera parameters (e.g., auto-exposure and  Covering an area of 300–1500 m which is further auto-gain). A wide range of calculations for managing these expandable by repeaters. issues have been proposed (for a late study). A top of the line International Journal of Scientific Engineering and Technology Research Volume.05, IssueNo.28, September-2016, Pages: 5985-5990 G. PRAVEEN, K. HARI, VENTRAPRAGADA TEJU IV. WORKING PRINCIPLE In the proposed system the detection of culprits in the defense can be made easy. As the term „Synergistic‟ means combining of two parameters so that efficiency to be improved. So in the proposed system matlab and embedded are combined to implement. Previously the recognized images are stored in database. The camera records the images in real time and are recognized by using recognition section & given to controller. It transmits the information through GPS. Whenever the unrecognized object is detected, it activates the alarm and sends information through GPS. Thus by using synergistic systems the unrecognized objects can be detected and tracked accurately.

A. Raspberry Pi Software Operating System: The Raspberry Pi primarily uses Linux kernel-based operating systems. The ARM11 is based on Fig.8.Receiver side INTRUDER FOUND message with version 6 of the ARM which is no longer supported by LOCATION longitude. several popular versions of Linux, including U buntu. The install manager for Raspberry Pi is NOOBS. The OSs included with NOOBS are:  Archlinux ARM  OpenELEC  Pidora (Fedora Remix)  Raspbmc and the XBMC open source digital media center  RISC OS – The operating system of the first ARM-based computer  Raspbian (recommended) – Maintained independently of the Foundation; based on ARM hard-float (armhf)- Debian 7 'Wheezy' architecture port, that was designed for a newer ARMv7 processor whose binaries would not work on the Rapberry Pi, but Raspbian is compiled for the ARMv6 instruction set of the Raspberry Pi making it work but with slower performance. It provides some Fig.9.Intruder Found Message At Transmission Side. available deb software packages, pre-compiled software bundles. A minimum size of 2 GB SD card is required, C. Run Times but a 4 GB SD card or above is recommended. There is a As a final remark, we would like to emphasize that the Pi Store for exchanging programs notable performance of our Bayesian loops comes without sacrificing efficiency: even with a high number of particles, B. Output Results such as 5000, the PF loop runs at 20 FPS without resorting to Output results of this paper is as shown in bellow Figs.7 to 9. multithreading or GPU optimizations, although parallelism could be easily exploited. This is not a secondary feature for an algorithm that deploys particle filtering, whose robustness usually comes at the expense of real-time processing. As for the Kalman filter loop, it runs comfortably on off-the-shelf hardware at 25 FPS. All the tests were performed on a PC equipped with an Intel Core i7 3 GHz and 6 GB of RAM ,running MS Windows 7 Professional.

V. CONCLUSION AND FUTURE SCOPE This thesis has been proposed with the aim of developing a low cost model for object identification and to carry out the estimation of motion analysis of the object. The problem of visual tracking, even in the simplified though widespread scenario of static cameras, is yet to be solved. In this paper, we have shown that significant advances can be reached by creating a principled communication flow between a Fig.7.Receiver Side o/p screen shot. recursive Bayesian estimator, such as the Kalman or PF, and International Journal of Scientific Engineering and Technology Research Volume.05, IssueNo.28, September-2016, Pages: 5985-5990 Visual Tracking in Image Streams Acquired by Static Cameras based on Change Detection by Raspberry Pi a Bayesian change detector. Accordingly, an observation [2] A. Yilmaz, O. Javed, and M. Shah, “Object tracking: A likelihood for the recursive filter is derived from the change survey,” ACMComput. Surv., vol. 38, no. 4, pp. 1–45, Dec. map without any hard-thresholding, while a cognitive 2006. feedback from the recursive filter steers the change detector. [3] I. Haritaoglu, D. Harwood, and L. S. Davis, “W4: Real- The proposed theoretical formulation relies on a remarkably time surveillanceof people and their activities,” IEEE Trans. simple model of the ideal change map given the target state, Pattern Anal. Mach. Intell.,vol. 22, no. 8, pp. 809–830, Aug. which encompasses the only two parameters of the overall 2000. computation. Several interesting extensions can be [4] R. T. Collins, A. J. Lipton, and T. Kanade, “A system for envisaged. The first issue we plan to investigate is how to videosurveillance and monitoring,” Robot.Inst., Carnegie formulate both communication flows to address multi target Mellon Univ.,Pittsburgh, PA, USA, Tech. Rep. 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Mach.Intell., vol. 31, no. 3, pp. 505–519, Mar. Future Scope: In this research work, the object identification 2009. and visual tracking has been done through the use of ordinary [12] J. Berclaz, F. Fleuret, E. Turetken, and P. Fua, “Multiple camera. The concept is well extendable in application like object trackingusing K-shortest paths optimization,” IEEE intelligent robots, automatic guided vehicle, enhancement of Trans. Pattern Anal. Mach.Intell., vol. 33, no. 9, pp. 1806– security system to detect the suspicious behavior along with 1819, Sep. 2011. detection of weapons, identify the suspicious movement of enemies on boarders with the help of night vision camera and Author’s Profile: many such applications. In the proposed method, background G. Praveen a Research Scholar currently subtraction technique has been used that is simple and fast. pursuing Masters in Technology with This technique is applicable where there is no movement of specialization in Embedded Systems from camera. For robotic application or automated vehicle Jawaharlal Nehru Institute of Technology, assistance system, due to the movement of camera, Ibrahimpatnam, Hyderabad affiliated to background are continuously changing leading to J.N.T.University, Hyderabad, Telangana, India. He obtained implementation of some different segment techniques like his Bachelor‟s degree in Electronics and Communication single Gaussian or multiple Gaussian models Engineering from Sri Indu College of Engineering and Technology ,Ibrahimpatnam, affiliated to J.N.T. University, VI. REFERENCES Hyderabad, Telangana, India. His research interests include [1] SamueleSalti, Member, IEEE, Alessandro Lanza, and Embedded Control Networks, Distributed Embedded Luigi Di Stefano, Member, IEEE, “Synergistic Change Systems, Critical Systems. He has a firm belief “Hard work Detection and Tracking”, IEEE Transactions on Circuits and and success go hand in hand”. Systems for Video Technology, Vol. 25, No. 4, April 2015.

International Journal of Scientific Engineering and Technology Research Volume.05, IssueNo.28, September-2016, Pages: 5985-5990 G. PRAVEEN, K. HARI, VENTRAPRAGADA TEJU K.Hari is an Assistant Professor in Jawaharlal Nehru Institute of Technology. He has teaching experience of 3 years. He holds a post graduate degree of M.Tech Electronics and Communication Engineering from Princeton College of Engineering and Technology, affiliated to J.N.T.UNIVERSITY, Hyderabad, India. He holds under graduate degree of B.Tech (ECE) from Swami Vivekananda Institute of Technology, affiliated to J.N.T.UNIVERSITY, Hyderabad, India.

V.Teju is an Associate Professor in Jawaharlal Nehru Institute of Technology.She has teaching experience of 10 years. She holds a post graduate degree of M.Tech (Embedded Systems) from St.Marys College of Engineering and Technology, Hyderabad affiliated to J.N.T.UNIVERSITY, Hyderabad, India. She holds under graduate degree of B.Tech (ECE) from Nova Engineering College, Jangareddygudem, west Godavari district, affiliated to J.N.T.University, Kakinada, India.

International Journal of Scientific Engineering and Technology Research Volume.05, IssueNo.28, September-2016, Pages: 5985-5990